Abstract
Historical data or real-world data (RWD) are often available in clinical trials, genetics, health care, psychology, environmental health, engineering, economics, and business. The power priors have emerged as a useful class of informative priors for a variety of situations in which historical data are available. In this presentation, various variations of the power priors are derived and discussed under a binomial regression model and a normal linear regression model. The data from the Kociba study and the National Toxicology Program (NTP) study as well as the data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) study are used to demonstrate the derivations of the power priors and their variations. A detailed analysis of the Kociba and NTP data and the ADNI data is carried out to further demonstrate the usefulness of the power priors and their variations in these real applications.
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Dr. Ming-Hui Chen is a Board of Trustees Distinguished Professor and Head of the Department of Statistics at the University of Connecticut (UConn). He obtained his PhD in statistics from Purdue University in 1993. He was elected to Fellow of American Association for the Advancement of Science (AAAS) in 2024, Fellow of International Society for Bayesian Analysis in 2016, Fellow of Institute of Mathematical Statistics in 2007, and Fellow of American Statistical Association in 2005. He received the UConn AAUP Research Excellence Award in 2013, the UConn College of Liberal Arts and Sciences (CLAS) Excellence in Research Award in the Physical Sciences Division in 2013, the UConn Alumni Association's University Award for Faculty Excellence in Research and Creativity (Sciences) in 2014, the ICSA Distinguished Achievement Award in 2020, and the Distinguished Science Alumni Award from Purdue University in 2023. He has published 475+ peer-reviewed journal articles and five books, including two advanced graduate-level books on Bayesian survival analysis and Monte Carlo methods in Bayesian computation. He has supervised 42+ PhD students. He served as President of ICSA (2013), Chair of the Eastern Asia Chapter of International Society for Bayesian Analysis (2018), President of New England Statistical Society (2018-2020), and the 2022 JSM Program Chair. Currently, he is Co Editor-in-Chief of Statistics and Its Interface, inaugurated Co Editor-in-Chief of New England Journal of Statistics in Data Science, and an Associate Editor for several other statistical journals.